Nonparametric confidence bands construction for GLM models with length biased data

被引：3

作者：

Ojeda, JL ^{[1
]}

Cristóbal, JA ^{[1
]}

Alcalá, JT ^{[1
]}

机构：

[1] Univ Zaragoza, Dept Stat Methods, E-50009 Zaragoza, Spain

来源：

JOURNAL OF NONPARAMETRIC STATISTICS | 2004年 / 16卷 / 3-4期

关键词：

confidence bands; nonparametric regression; generalized linear models; length biased data; supremum distribution for Gaussian processes;

D O I：

10.1080/10485250310001634746

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

In this work, we propose a nonparametric confidence bands construction for the linear predictor in generalized linear models (GLM) when data is affected by length bias. These confidence bands are suitable to keep track of the behavior of the linear predictor for a given GLM family and link. To that end we adapt the result of Bickel, P. J. and Rosenblatt, M. (1973) about the supremum for stationary Gaussian processes.

引用

页码：421 / 441

页数：21

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